DC programming and DCA for dictionary learning

Abstract

Sparse representations of signals based on learned dictionaries have drawn considerable interest in recent years. However, the design of dictionaries adapting well to a set of training signals is still a challenging problem. For this task, we propose a novel algorithm based on DC (Difference of Convex functions) programming and DCA(DCAlgorithm). The efficiency of proposed algorithm will be demonstrated in image denoising application.